The Pittsburgh Sleep Quality Index (PSQI) is a widely used measure of sleep quality in adolescents, but information regarding its psychometric strengths and weaknesses in this population is limited. In particular, questions remain regarding whether it measures one or two sleep quality domains. The aims of the present study were to (a) adapt the PSQI for use in adolescents and young adults, and (b) evaluate the psychometric properties of the adapted measure in this population. The PSQI was slightly modified to make it more appropriate for use in youth populations and was translated into Spanish for administration to the sample population available to the study investigators. It was then administered with validity criterion measures to a community-based sample of Spanish adolescents and young adults (AYA) between 14 and 24 years old (N = 216). The results indicated that the questionnaire (AYA-PSQI-S) assesses a single factor. The total score evidenced good convergent and divergent validity and moderate reliability (Cronbach's alpha = .72). The AYA-PSQI-S demonstrates adequate psychometric properties for use in clinical trials involving adolescents and young adults. Additional research to further evaluate the reliability and validity of the measure for use in clinical settings is warranted.

Evidence supports the efficacy of hypnotic treatments, but there remain many unresolved questions regarding how hypnosis produces its beneficial effects. Most theoretical models focus more or less on biological, psychological, and social factors. This scoping review summarizes the empirical findings regarding the associations between specific factors in each of these domains and response to hypnosis. The findings indicate that: (1) no single factor appears primary; (2) different factors may contribute more or less to outcomes in different subsets of individuals or for different conditions; and (3) comprehensive models of hypnosis that incorporate factors from all 3 domains may ultimately prove to be more useful than more restrictive models that focus on 1 or a very few factors.

The findings confirm the importance of pain-related activity management patterns as predictors of patient function, and support the necessity of addressing these factors in chronic pain treatment. In addition, the results suggest that targeting increases in activity pacing and decreases in pain avoidance, specifically, might yield the best patient outcomes. However, further research to evaluate this possibility is necessary.